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Record W2056777612 · doi:10.1115/1.4001215

Position-Error Based Schemes for Bilateral Teleoperation With Time Delay: Theory and Experiments

2010· article· en· W2056777612 on OpenAlexafffund
Ilia G. Polushin, Peter Liu, Chung–Horng Lung, Gia Dien On

Bibliographic record

VenueJournal of Dynamic Systems Measurement and Control · 2010
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsCarleton UniversityWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTeleoperationControl theory (sociology)Stability (learning theory)Position (finance)Computer scienceTransparency (behavior)TeleroboticsSmall-gain theoremRobotControl (management)Artificial intelligenceMobile robot

Abstract

fetched live from OpenAlex

The problem of stable bilateral teleoperation with position-error based force feedback in the presence of time-varying possibly unbounded communication delay is addressed. Two stabilization schemes are proposed that guarantee “independent of delay” stability of the teleoperator system. In particular, one of the schemes theoretically allows to achieve an arbitrary high force-reflection gain, which leads to better transparency without sacrificing the stability of the overall system. The stability analysis is based on the input-to-output stable small gain theorem for systems of functional-differential equations. Experimental results are presented, which demonstrate stable behavior of the telerobotic system with time-varying communication delay during contact with a rigid obstacle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.207
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2010
Admission routes2
Has abstractyes

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